I have been going to national parks literally every year since I was born. I was raised mostly in Utah and my family and I would make sure to visit different parks at least once or twice a year. As I got older, I started to see that these parks were getting overcrowded and less attractive. Even though I still hold a nostalgic love and respect for many of these parks, my family and I now seek to enjoy nature in more isolated places.
So why did these parks become so increasingly popular? In my opinion, National parks are a great way for people to get out and and enjoy nature in a ‘casual’ sense. Prime example, Zion’s National Park provides great hiking trails for mostly beginner to novice hikers while providing amenities such as resort-like lodging and restaurants. They even established a shuttle transportation system around the park so people wouldn’t have to “hike-to-the-hike.” While it does still offer some opportunities for the more experienced and adventurous, it is now a huge hotspot for casuals.
Although these National Parks have now gotten more and more crowded, I would still like to visit them in the future. The primary purpose of my project was to analyze the parks’ statistics and then find data to determine what time of year would be ideal for me to visit them.
Here we see that Grand Canyon National Park is in the lead by a huge margin, having over 6 million people in 2 consecutive years. It’s also important to note that during approximately 2012 and 2013 all parks, except Arches and Capitol Reef, seemed to have experienced a huge exponential growth in yearly visitation. The sudden exponential decay of visitation rates in 2020 was due to the Covid-19 Pandemic.
I fitted a linear model (estimated using ML) to predict YearlyVis with Hotels, Hikes, Distance_from_Major_City.mi, CampUnits and Size_acres (formula: YearlyVis ~ Hotels + Hikes + Distance_from_Major_City.mi + CampUnits + Size_acres). The model’s explanatory power is substantial (R2 = 0.74). The model’s intercept, corresponding to Hotels = 0, Hikes = 0, Distance_from_Major_City.mi = 0, CampUnits = 0 and Size_acres = 0, is at 5.89e+05 (95% CI [5.11e+05, 6.67e+05], t(3522) = 14.86, p < .001). Results within this model:
Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using
Conclusion: The results of the model seem consistent and realistic. Hotels and Camp units were not included in the model because I couldn’t connect dates to them. Furthermore, it’s interesting to point out that Grand Canyon National Park was never the highest or lowest in any of the categories, but still has the highest yearly visitation rate.
My ideal conditions are: 1. Around 50 degrees average temperature. 2. Not over 3 inches of precipitation in past months. 3. Least amount of people that fit into the first two paramters.
Result: November
Result: April or October
Result: March
Result: April or October
Result: April or October
Result: September
Result: April or November
AllTrails: Trail Guides & Maps for hiking, camping, and running. AllTrails.com. (n.d.). Retrieved December 13, 2021, from https://www.alltrails.com/.
U.S. Department of the Interior. (n.d.). Nps.gov homepage (U.S. National Park Service). National Parks Service. Retrieved December 13, 2021, from https://www.nps.gov/index.htm.
National Centers for Environmental Information (NCEI). (n.d.). Retrieved December 13, 2021, from https://www.ncei.noaa.gov/.
Expedia travel: Vacation Homes, hotels, car rentals, Flights & More. Expedia.com. (n.d.). Retrieved December 13, 2021, from https://www.expedia.com/.
Other information was searched though google.com